In currently available media systems, a recommendation system may monitor information associated with actors to determine which actors to recommend. Given the plethora of actors, it is resource intensive to continuously monitor information associated with a huge data set of actors when selecting actors that are worth recommending. On the other hand, if the recommendation system monitors changes in actor information infrequently, the recommendation system may miss out on recommending actors who have recently become prominent and thus may not perform as well as other recommendation systems. Thus, current recommendation systems can be improved upon to optimize both the computational resource requirements and system performance. Furthermore, in some instances, a user may only be interested in content segments in which a recommended actor appears and in which the actor's quality of acting (e.g., good, bad, mediocre) is a pre-specified quality of acting. Current systems are limited to providing a user with content segments in which a selected actor appears and thus can be improved upon to provide content that is more customized to a user's preferences.